Name: Sina Faezi
Chair: Dr. Mohammad Al Faruque
Date: April 21, 2021
Time: 10:00 AM
Committee: Dr. Mohammad Al Faruque (UCI), Dr. Philip Brisk (UCR), Dr. Zhou Li (UCI)
Title: “Data-Driven Modeling and Analysis for Trustworthy Cyber-Physical Systems”
In the age of digitization, a layer of cyber software sits on a hardware circuit and controls the physical systems around us. The tight integration of cyber and physical components is referred to as Cyber-Physical Systems (CPS). The interaction between cyber and physical components brings unique challenges which traditional modeling tools struggle to resolve. Particularly, they often fail to model the unintentional physical manifestation of cyber-domain information flows (side-channel signals) which may result in trust issues in the system.
In this thesis, we take a data-driven approach to model a CPS behavior when it is exposed to various information flows. First, we demonstrate how it is possible to extract valuable cyber-domain information by recording the acoustic noise generated by a DNA synthesizer. Then, we consider an integrated circuit as a CPS by itself and monitor the chip through electromagnetic and power side-channels to detect hardware Trojans (HT) in the chip.
HT is a malicious modification of the hardware implementation of a circuit design which may lead to various security issues over the life-cycle of a chip. One of the major challenges for HT detection is its reliance on a trusted reference chip (a.k.a golden chip). However, in practice, manufacturing a golden chip is costly and often considered infeasible. This thesis investigates a creative neural network design and training methodology which eliminates the need for a golden chip. Furthermore, it proposes using hierarchical temporal memory (HTM) as a data driven approach which can be updated over the chip’s life-cycle and uses that for run-time HT detection.
Bio: Sina Faezi is a Ph.D. candidate in computer engineering at the University of California, Irvine (UCI). He works under Professor M. Al Faruque in the Autonomous and Intelligent Cyber-Physical Systems (AICPS) laboratory on the topic of data-driven modeling and analysis for Cyber-Physical systems. He creates data-driven models and then uses them to tackle practical issues like durability, security, process control, etc., in cyber-physical systems. Through his Ph.D., he has published numerous articles in prestigious conferences and has received Broadcom Foundation Graduate Engineering fellowship. He has completed his B.Sc. in electrical engineering at the Sharif University of Technology in 2015 and has received his M.S. degree in computer engineer from UCI in 2017.